Presenting a Social Value Database and Simulator for Public Health

Abstract Background There is increasing recognition that Public Health Institutes need to build on the traditional value for money approach, to find ways to capture, measure and show the full range of their outcomes, impacts and related value. As part of a drive to measure value and impact in public health and demonstrate how investment in health can contribute to an Economy of Well-being, Public Health Wales has developed an interactive database to capture and illustrate the social value of public health services and interventions. Methods Scoping reviews of both academic and grey literature were undertaken to populate a database of health economics evaluations of public health interventions, focusing on Social Return on Investment (SROI). In addition, a simulated methodology was developed which allows the evidence to be manipulated and made relevant to individual contexts to help inform investment decisions at a local level. Results To date, the database has accumulated an excess of 50 SROI evaluations of various public health interventions, across areas including mental health, behaviour change, physical activity, nutrition, employment and primary care. The evaluations are based on European and International contexts, are published in both grey and academic sources, and are of varying quality. Conclusions SROI is a credible method for measuring the value of wider social, economic and environment outcomes achieved from public health interventions. The Social Value Database and Simulator presents a collation of studies and analysis utilising innovative health economics methods. Key messages • Public Health Wales’ Social Value Database and Simulator collates economic evaluations of public health interventions, to be used by policy makers to enable improved investment in health and well-being. • Social Return on Investment is a credible method for measuring the wider impact created by public health interventions.


Background:
There is increasing recognition that Public Health Institutes need to build on the traditional value for money approach, to find ways to capture, measure and show the full range of their outcomes, impacts and related value. As part of a drive to measure value and impact in public health and demonstrate how investment in health can contribute to an Economy of Well-being, Public Health Wales has developed an interactive database to capture and illustrate the social value of public health services and interventions. Methods: Scoping reviews of both academic and grey literature were undertaken to populate a database of health economics evaluations of public health interventions, focusing on Social Return on Investment (SROI). In addition, a simulated methodology was developed which allows the evidence to be manipulated and made relevant to individual contexts to help inform investment decisions at a local level.

Results:
To date, the database has accumulated an excess of 50 SROI evaluations of various public health interventions, across areas including mental health, behaviour change, physical activity, nutrition, employment and primary care. The evaluations are based on European and International contexts, are published in both grey and academic sources, and are of varying quality. Conclusions: SROI is a credible method for measuring the value of wider social, economic and environment outcomes achieved from public health interventions. The Social Value Database and Simulator presents a collation of studies and analysis utilising innovative health economics methods. Key messages: Public Health Wales' Social Value Database and Simulator collates economic evaluations of public health interventions, to be used by policy makers to enable improved investment in health and well-being. Social Return on Investment is a credible method for measuring the wider impact created by public health interventions.

Background:
The validity of self-reported disease prevalence estimates in health surveys may be low when compared to data from medical records in administrative registers. Such discrepancies reflect a low content validity of the survey question, which may ultimately compromise the application of these survey data for public health purposes. The aim of the present study was to examine the agreement of self-reports of seven diseases with data from administrative registers, both overall and by sociodemographic characteristics.

Methods:
Prevalence estimates of self-reported current and/or previous diabetes, asthma, rheumatoid arthritis, osteoporosis, myocardial infarction, apoplexy, and cancer, respectively, were derived from the Danish National Health Survey in 2017 (n = 183,372 adults aged 16 years). Individual-level data were linked to registry data on the same diseases. Sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), kappa, and total agreement between self-reported and registry-documented prevalence estimates were examined.

Results:
For all included diseases, the specificity was >92%, and the sensitivity varied between 59% (cancer) and 95% (diabetes). NPV was >94% for all diseases and PPV varied between 13% (rheumatoid arthritis) and 93% (cancer). Total agreement varied between 91 % (asthma) and 99% (diabetes), whereas kappa was lowest for rheumatoid arthritis (0.21) and highest for diabetes (0.88). Sociodemographic variables were significantly associated with total agreement with sex, age, and educational level exhibiting the strongest associations.

Conclusions:
Overall, total agreement, specificity, and NPV between selfreported and registry-documented disease prevalence estimates are high, but PPV and kappa vary greatly between diseases. The latter findings reflect a low content validity of the applied survey question for specific diseases. This should be taken into account when interpreting similar results from surveys.

Key messages:
The validity of self-reported disease prevalence estimates may be low when compared to data from medical records. We found positive predictive values and kappa to vary greatly between diseases. Future studies should aim at designing survey questions properly in order to ensure a high content validity of the applied question.